Tootfinder

who up putting linux and tensorflow in their lightbulbs

ANIRA: An Architecture for Neural Network Inference in Real-Time Audio Applications
Valentin Ackva, Fares Schulz
https://arxiv.org/abs/2506.12665 https://

ANIRA: An Architecture for Neural Network Inference in Real-Time Audio Applications
Numerous tools for neural network inference are currently available, yet many do not meet the requirements of real-time audio applications. In response, we introduce anira, an efficient cross-platform library. To ensure compatibility with a broad range of neural network architectures and frameworks, anira supports ONNX Runtime, LibTorch, and TensorFlow Lite as backends. Each inference engine exhibits real-time violations, which anira mitigates by decoupling the inference from the audio callback…

Performance Portable Gradient Computations Using Source Transformation
Kim Liegeois, Brian Kelley, Eric Phipps, Sivasankaran Rajamanickam, Vassil Vassilev
https://arxiv.org/abs/2507.13204

Performance Portable Gradient Computations Using Source Transformation
Derivative computation is a key component of optimization, sensitivity analysis, uncertainty quantification, and nonlinear solvers. Automatic differentiation (AD) is a powerful technique for evaluating such derivatives, and in recent years, has been integrated into programming environments such as Jax, PyTorch, and TensorFlow to support derivative computations needed for training of machine learning models, resulting in widespread use of these technologies. The C++ language has become the de fa…

Statistical Quality and Reproducibility of Pseudorandom Number Generators in Machine Learning technologies
Benjamin A. Antunes (LIRMM | DALI)
https://arxiv.org/abs/2507.03007 ht…